Cards are a common organizing unit for modern user interfaces (UI). At their core, they’re just rectangular containers with borders and padding. However, when utilized properly to group related information, they help users better digest, engage, and navigate through content. This is why most successful dashboard/UI frameworks make cards a core feature of their component library. This article provides an overview of the API that bslib provides to create Bootstrap cards.
Setup code
To demonstrate that bslib cards work outside of Shiny (i.e., in R Markdown, static HTML, etc), we’ll make repeated use of statically rendered htmlwidgets like plotly and leaflet. Here’s some code to create those widgets:
library(bslib)
library(shiny)
library(htmltools)
library(plotly)
library(leaflet)
plotly_widget <- plot_ly(x = diamonds$cut) %>%
config(displayModeBar = FALSE) %>%
layout(margin = list(t = 0, b = 0, l = 0, r = 0))
leaflet_widget <- leafletOptions(attributionControl = FALSE) %>%
leaflet(options = .) %>%
addTiles()Shiny usage
Cards work equally well in Shiny. In the
examples below, replace plotly_widget with
plotlyOutput() and leaflet_widget with
leafletOutput() to adapt them for Shiny server-rendered
plots/maps.
Hello card()
A card() is designed to handle any number of “known”
card items (e.g., card_header(), card_body(),
etc) as unnamed arguments (i.e., children). As we’ll see shortly,
card() also has some useful named arguments (e.g.,
full_screen, height, etc).
At their core, card() and card items are just an HTML
div() with a special Bootstrap class, so you can use
Bootstrap’s utility classes to customize things like colors,
text, borders,
etc.
card(
card_header(
class = "bg-dark",
"A header"
),
card_body(
markdown("Some text with a [link](https://github.com)")
)
)Some text with a link
Implicit card_body()
If you find yourself using card_body() without changing
any of its defaults, consider dropping it altogether since any direct
children of card() that aren’t “known” card()
items, are wrapped together into an implicit card_body()
call.1
For example, the code to the right generates HTML that is identical to
the previous example:
card(
card_header(
class = "bg-dark",
"A header"
),
markdown("Some text with a [link](https://github.com).")
)Some text with a link.
Restricting growth
By default, a card()’s size grows to accommodate the
size of it’s contents. Thus, if a card_body() contains a
large amount of text, tables, etc., you may want to specify a
height or max_height. That said, when laying
out multiple cards, it’s likely best not
to specify height on the card(), and instead, let the
layout determine the height layout_column_wrap().
Although scrolling is convenient for reducing the amount of space
required to park lots of content, it can also be a nuisance to the user.
To help reduce the need for scrolling, consider pairing scrolling with
full_screen = TRUE (which adds an icon to expand the card’s
size to the browser window). Notice how, when the card is expanded to
full-screen, max_height/height won’t effect
the full-screen size of the card.
card(
max_height = 250,
full_screen = TRUE,
card_header(
"A long, scrolling, description"
),
lorem::ipsum(paragraphs = 3, sentences = 5)
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Filling outputs
A card()’s default behavior is optimized for
facilitating filling layouts. More
specifically, if a fill item (e.g.,
plotly_widget), appears as a direct child of a
card_body(), it resizes to fit the card()s
specified height. This means, by specifying height = 250
we’ve effectively shrunk the plot’s height from its default of 400 down
to about 200 pixels. And, when expanded to full_screen, the
plot grows to match the card()’s new size.
card(
height = 250,
full_screen = TRUE,
card_header("A filling plot"),
card_body(plotly_widget)
)Most htmlwidgets (e.g., plotly, leaflet, etc) and some other Shiny
output bindings (e.g, plotOutput(),
imageOutput(), etc) are fill items by
default, so this behavior “just works” in those scenarios. And, in some
of these situations, it’s helpful to remove card_body()’s
padding, which can be done via spacing
& alignment utility classes.
card(
height = 275,
full_screen = TRUE,
card_header("A filling map"),
card_body(
class = "p-0",
leaflet_widget
),
card_footer(
class = "fs-6",
"Copyright 2023 RStudio, PBC"
)
)Fill item(s) aren’t limited in how much they grow
and shrink, which can be problematic when a card becomes very small. To
work around this, consider adding a min_height on the
card_body() container. For example, try using the handle on
the lower-right portion of this card example to make the card
taller/smaller.
This interactive example is a bit contrived in that we’re using CSS
resize to demonstrate how to make plots that don’t shrink beyond a
certain point, but this concept becomes quite useful when implementing
page-level filling layouts (i.e.,
page_fillable()) with multiple
cards.
card(
height = 300,
style = "resize:vertical;",
card_header("Plots that grow but don't shrink"),
card_body(
min_height = 250,
plotly_widget,
plotly_widget
)
)Troubleshooting fill
As you’ll learn more about in filling
layouts, a fill item loses its ability to fill when
wrapped in additional UI element that isn’t a fillable
container. To fix the situation, use as_fill_carrier() to
allow the additional element to carry the potential to fill from the
card_body() down to the fill item.
Multiple card_body()
A card() can have multiple card_body()s,
which is especially useful for:
- Combining both resizable and non-resizable contents (i.e., fill items and non-fill).
- Allowing each
card_body()to have their own styling (via inline styles and/or utility classes) and resizing limits (e.g.,min_height).
For example, when pairing filling output with scrolling content, you
may want min_height on the filling output since the
scrolling content will force it to shrink:
card(
height = 375,
full_screen = TRUE,
card_header(
"Filling plot, scrolling description"
),
card_body(
min_height = 200,
plotly_widget
),
card_body(
class = "lead container",
lorem::ipsum(paragraphs = 10, sentences = 5)
)
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Also, when the content has a fixed size, and should not be allowed to
scroll, set fill = FALSE:
card(
height = 350,
full_screen = TRUE,
card_header(
"Filling plot, short description"
),
plotly_widget,
card_body(
fill = FALSE,
card_title("A subtitle"),
p(class = "text-muted", "And a caption")
)
)A subtitle
And a caption
Multiple columns
As you’ll learn in column-based
layouts, layout_column_wrap() is great for multi-column
layouts that are responsive and accommodate for filling output. Here we have an equal-width
2-column layout using width = 1/2, but it’s also possible
to have varying column
widths.
card(
height = 350,
full_screen = TRUE,
card_header("A multi-column filling layout"),
card_body(
min_height = 200,
layout_column_wrap(
width = 1/2,
plotOutput("p1"),
plotOutput("p2")
)
),
lorem::ipsum(paragraphs = 3, sentences = 5)
)Lorem curae consequat curabitur malesuada interdum: senectus sapien tempus venenatis. Varius malesuada volutpat id potenti curae; dui dapibus habitasse ligula. Ut habitasse non, curae scelerisque cras diam: primis sociosqu – commodo netus. Dictum primis morbi fusce tempor molestie, venenatis purus. Ultrices commodo gravida mollis posuere, taciti venenatis aptent pharetra inceptos vitae a, accumsan cum penatibus vehicula nostra?
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Multiple cards
layout_column_wrap() is especially nice for laying out
multiple cards since each card in a particular row will have the same
height (by default). Learn more in column-based layouts.
layout_column_wrap(
width = 1/2,
height = 300,
card(full_screen = TRUE, card_header("A filling plot"), plotly_widget),
card(full_screen = TRUE, card_header("A filling map"), card_body(class = "p-0", leaflet_widget))
)Multiple tabs
navset_card_tab() and navset_card_pill()
make it possible to create cards with multiple tabs or pills. These
functions have the same full_screen capabilities as normal
card()s as well some other options like title
(since there is no natural place for a card_header() to be
used). Note that, each nav_panel() object is similar to a
card(). That is, if the direct children aren’t already card
items (e.g., card_title()), they get implicitly wrapped in a
card_body().
library(leaflet)
navset_card_tab(
height = 450,
full_screen = TRUE,
title = "HTML Widgets",
nav_panel(
"Plotly",
card_title("A plotly plot"),
plotly_widget
),
nav_panel(
"Leaflet",
card_title("A leaflet plot"),
leaflet_widget
),
nav_panel(
shiny::icon("circle-info"),
markdown("Learn more about [htmlwidgets](http://www.htmlwidgets.org/)")
)
)Sidebars
As you’ll learn more about in sidebar
layouts, layout_sidebar() just works when placed inside
in a card(). In this case, if you want fill
items (e.g., plotly_widget) to still fill the card
like we’ve seen before, you’ll need to
set fillable = TRUE in layout_sidebar().
card(
height = 300,
full_screen = TRUE,
card_header("A sidebar layout inside a card"),
layout_sidebar(
fillable = TRUE,
sidebar = sidebar(
actionButton("btn", "A button")
),
plotly_widget
)
)Static images
card_image() makes it easy to embed static (i.e.,
pre-generated) images into a card. Provide a URL to href to
make it clickable. In the case of multiple card_image()s,
consider laying them out in multiple cards
with layout_column_wrap() to produce a grid of clickable
thumbnails.
card(
height = 300,
full_screen = TRUE,
card_image(
file = "shiny-hex.svg",
href = "https://github.com/rstudio/shiny"
),
card_body(
fill = FALSE,
card_title("Shiny for R"),
p(
class = "fw-light text-muted",
"Brought to you by RStudio."
)
)
)
Shiny for R
Brought to you by RStudio.
Flexbox
Both card() and card_body() default to
fillable = TRUE (that is, they are CSS flexbox
containers), which works wonders for facilitating filling outputs, but it also leads to
surprising behavior with inline tags (e.g., actionButton(),
span(), strings, etc). Specifically, each inline tag is
placed on a new line, but in a “normal” layout flow
(fillable = FALSE), inline tags render inline.
card(
card_body(
fillable = TRUE,
"Here's some", tags$i("inline"), "text",
actionButton("btn1", "A button")
),
card_body(
fillable = FALSE,
"Here's some", tags$i("inline"), "text",
actionButton("btn2", "A button")
)
)That said, sometimes working in a flexbox layout is quite useful,
even when working with inline tags. Here we leverage flexbox’s gap
property to control the spacing between a plot, a (full-width) button,
and paragraph. Note that, by using markdown() for the
paragraph, it wraps the results in a <p> tag, which
means the contents of the paragraph are not longer subject to
flexbox layout. If we wanted, we could do something similar to render
the actionButton() inline by wrapping it in a
div().
card(
height = 325, full_screen = TRUE,
card_header("A plot with an action links"),
card_body(
class = "gap-2 container",
plotly_widget,
actionButton(
"go_btn", "Action button",
class = "btn-primary rounded-0"
),
markdown("Here's a _simple_ [hyperlink](https://www.google.com/).")
)
)Here's a simple hyperlink.
In addition to gap, flexbox has really nice ways of handling otherwise difficult spacing and alignment issues. And, thanks to Bootstrap’s flex utility classes, we can easily opt-in and customize defaults.
card(
height = 300, full_screen = TRUE,
card_header(
class = "d-flex justify-content-between",
"Centered plot",
checkboxInput("check", " Check me", TRUE)
),
card_body(
class = "align-items-center",
plotOutput("id", width = "75%")
)
)Shiny
Since this article is statically rendered, the examples here use
statically rendered content/widgets, but the same card()
functionality works for dynamically rendered content via Shiny (e.g.,
plotOutput(), plotlyOutput(), etc).
An additional benefit that comes with using shiny is the ability to
use getCurrentOutputInfo() to render new/different content
when the output container becomes large enough, which is particularly
useful with card(full_screen = T, ...). For example, you
may want additional captions/labels when a plot is large, additional
controls on a table, etc (see the value
boxes article for a clever use of this).
# UI logic
ui <- page_fluid(
card(
max_height = 200,
full_screen = TRUE,
card_header("A dynamically rendered plot"),
plotOutput("plot_id")
)
)
# Server logic
server <- function(input, output, session) {
output$plot_id <- renderPlot({
info <- getCurrentOutputInfo()
if (info$height() > 600) {
# code for "large" plot
} else {
# code for "small" plot
}
})
}
shinyApp(ui, server)Appendix
The following CSS is used to give plotOutput() a
background color; it’s necessary here because this documentation page is
not actually hooked up to a Shiny app, so we can’t show a real plot.